Information Gap Decision Theory Based Congestion and Voltage Management in the Presence of Uncertain Wind Power

Title: Information Gap Decision Theory Based Congestion and Voltage Management in the Presence of Uncertain Wind Power
Authors: Murphy, Conor
Soroudi, Alireza
Keane, Andrew
Permanent link: http://hdl.handle.net/10197/7249
Date: 29-Nov-2015
Online since: 2015-12-01T16:44:35Z
Abstract: The supply of electrical energy is being increasinglysourced from renewable generation. The variability anduncertainty of renewable generation, compared to a dispatchableplant, is a significant dissimilarity of concern to the traditionallyreliable and robust power system. This change is driving thepower system towards a more flexible entity that carries greateramounts of reserve. For congestion management purposes itis of benefit to know the probable and possible renewablegeneration dispatch, but to what extent will these variations effectthe management of congestion on the system? Reactive powergeneration from wind generators and demand response flexibilityare the decision variables here in a risk averse multi-periodAC optimal power flow (OPF) seeking to manage congestionon distribution systems. Information Gap Decision Theory isused to address the variability and uncertainty of renewablegeneration. In addition, this work considers the natural benefitsto the congestion on a system from the over estimation of windforecast; providing an opportunistic schedule for both demandresponse nodes and reactive power provision from distributedgeneration.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Sustainable Energy
Volume: 7
Issue: 2
Start page: 841
End page: 849
Copyright (published version): 2015 IEEE
Keywords: Congestion managementDistributed power generationInformation gap decision theoryOptimizationReactive power
DOI: 10.1109/TSTE.2015.2497544
Language: en
Status of Item: Peer reviewed
Appears in Collections:Electrical and Electronic Engineering Research Collection

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